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ANGHEL Andrei

« High-Resolution Time-Frequency SAR Signal Processing for Large Infrastructure Monitoring ».

 

Directeur de thèse :     Cornel IOANA

Co-encadrant :     Gabriel VASILE

École doctorale : Electronique, electrotechnique, automatique, traitement du signal (eeats)

Spécialité : Signal, image, parole, télécoms

Structure de rattachement : Grenoble-INP

Établissement d'origine : Université Polytechnique de Bucarest

Financement(s) : contrat à durée déterminée ; contrat à durée déterminée ; contrat à durée déterminée

 

Date d'entrée en thèse : 01/10/2012

Date de soutenance : 08/10/2015

 

Composition du jury :
M. Laurent POLIDORI, Professeur, CNAM, Rapporteur
M. Hugh GRIFFITHS, Professeur, University College London, Rapporteur
M. Ljubisa STANKOVIC, Professeur, Université du Monténégro, Examinateur
M. Marc LESTURGIE, Ingénieur expert, HdR, ONERA et SONDRA, Examinateur
M. Remus CACOVEANU, Maître de conférence, Université Polytechnique de Bucarest, Examinateur
M. Rémy BOUDON, Ingénieur expert, EDF DTG, Membre invité
M. Cornel IOANA, Maître de conférence, HdR, Grenoble INP, Directeur de thèse
M. Silviu CIOCHINA, Professeur, Université Polytechnique de Bucarest, Co-Directeur de thèse
M. Gabriel VASILE, Chargé de recherche, CNRS, Encadrant

 

Résumé : The thesis is composed of two research axis. The first one consists in proposing time-frequency signal processing tools for frequency modulated continuous wave (FMCW) radars used for displacements measurements, while the second one consists in designing a spaceborne synthetic aperture radar (SAR) signal processing methodology for infrastructure monitoring when an external point cloud of the envisaged structure is available. In the first part of the thesis, we propose our solutions to the nonlinearity problem of an X-band FMCW radar designed for millimetric displacement measurements of short-range targets. The nonlinear tuning curve of the voltage controlled oscillator from the transceiver can cause a dramatic resolution degradation for wideband sweeps. To mitigate this shortcoming, we have developed two time warping-based methods adapted to wideband nonlinearities: one estimates the nonlinear terms using the high order ambiguity function, while the other is an autofocus approach which exploits the spectral concentration of the beat signal. Onwards, as the core of the thesis, we propose a novel method for scattering centers detection and tracking in spaceborne SAR images adapted to infrastructure monitoring applications. The method is based on refocusing each SAR image on a provided 3D point cloud of the envisaged infrastructure and identifying the reliable scatterers to be monitored by means of four dimensional (4D) tomography. The refocusing algorithm is compatible with stripmap, spotlight and sliding spotlight SAR images and consists of an azimuth defocusing followed by a modified back-projection algorithm on the given set of points which exploits the time-frequency structure of the defocused azimuth signal. The scattering centers of the refocused image are detected in the 4D tomography framework by testing if the main response is at zero elevation in the local elevation-velocity spectral distribution obtained using the Capon estimator. The mean displacement velocity is estimated from the peak response on the zero elevation axis, while the displacements time series for detected single scatterers is computed as phase difference of complex amplitudes. Finally, we present the measurement campaigns carried out on the Puylaurent water-dam and the Chastel landslide using GPS measurements, topographic surveys and laser scans to generate the point clouds of the two structures. The comparison between in-situ data and the results obtained by combining TerraSAR-X data with the generated point clouds validate the developed SAR signal processing chain.


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